finco                 package:dprep                 R Documentation

_F_I_N_C_O _F_e_a_t_u_r_e _S_e_l_e_c_t_i_o_n _A_l_g_o_r_i_t_h_m

_D_e_s_c_r_i_p_t_i_o_n:

     This function selects features using the FINCO algorithm. The
     dataset must contain only discretized values.

_U_s_a_g_e:

     finco(data, level)

_A_r_g_u_m_e_n_t_s:

    data: name of the dataset containing the discretized values

   level: minimum inconsistency level

_D_e_t_a_i_l_s:

     The level value must be greater than the inconsistency of the
     whole dataset, which first must be discretized. The function
     inconsist included in this library  computes inconsistencies. A
     small value of level yields a greater number of selected features.

_V_a_l_u_e:

varselec: index of selected features

inconsis: inconsistency rates of the selected features

_A_u_t_h_o_r(_s):

     Edgar Acuna

_R_e_f_e_r_e_n_c_e_s:

     Acuna, E , (2003) A comparison of filters and wrappers for feature
     selection in supervised classification. Proceedings of  the
     Interface 2003 Computing Science and Statistics. Vol 34.

     Acuna, E., Coaquira, F. and Gonzalez, M. (2003). A comparison of
     feature selection  procedures for classifiers based on kernel
     density estimation. Proc. of the Int. Conf. on Computer, 
     Communication and Control technologies, CCCT03. VolI. p. 468-472.
     Orlando, Florida.

_S_e_e _A_l_s_o:

     'inconsist','lvf'

_E_x_a_m_p_l_e_s:

     #---- Feature Selection with FINCO
     data(my.iris)
     disciris=disc.ew(my.iris,1:6)
     inconsist(disciris)
     finco(disciris,0.05)

